A typical detector array of an image signal processing system provides spatial image pattern acquisition, conversion, and readout. Most prior art detector arrays simultaneously capture and convert image data at individual elements and sequentially output the array contents. Sequential readout of the entire array limits the frame rate (how often the array can be read out per unit time) that can be achieved. Therefore, applications requiring high frame rates are throughput limited by the readout circuitry. Some prior art detector arrays use parallel output lines or random address architectures to improve array readout speed. Such random access detector arrays provide fast readout of predetermined detector regions. However, the entire detector array must first be scanned in full to locate regions of interest Therefore, the total frame rate is still limited.
High speed operation, parallel output structures, or random access addressing architectures improves performance. By providing higher detector output rates, these approaches achieve fast frame rates and are thus useable in rapidly changing image environments. However, these approaches do not reduce the volume of data to be output from the detector array and, consequently, the time required to read the contents of the array is proportional to the array size, for a given frame access rate. As the size of the detector array increases, a corresponding increase in the output rate (given the same architecture) is required to maintain the same frame access rate. Subsequent processing is also required to remove unwanted data (i.e. data not corresponding to an active image of interest) from the output. Moreover, removal of unwanted data does not increase array readout speed, but rather only reduces the data volume for subsequent processing.
Prior methods for locating objects of interest in the data from random access arrays typically use information obtained from previous full scans of the array to track the object. Data access based on previous information increases readout speed and reduces output data requirements for stationary or slowly changing objects. However, for this technique to be effective, future object positions must be predictable from previously known position information. Previous information is not always available for predictions; for instance, such information is not available if a new frame of data is uncorrelated with previous frames. Uncorrelated data occurs when an object changes location within the detector array at a speed approaching or exceeding the readout cycle rate.